Stratifying colorectal cancer liver metastases using unsupervised clustering of quantitative imaging phenotypes

Personalized and precise treatments are the keys to improve prognosis of cancer patients and are also the main strategy of Sunnybrook Hospital. This project aims to stratify patients with colorectal cancer liver metastases (CRM) based on their disease subtype and risk using magnetic resonance imaging, which is routinely used in the diagnosis, staging and operative planning. Machine learning models that identify subtypes of CRM will be built By understanding how and why CRM differs in different groups of patients, scientists and clinicians can better understand how CRM develop and how to better match CRM patients to the targeted therapy most likely to cure their disease. This research will be vital for improving the care and treatment of CRM patients in Sunnybrook hospital.

Faculty Supervisor:

Anne Martel


Jianan Chen


Vector Institute




Professional, scientific and technical services


University of Toronto



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